Least Squares Support Vector Machine Classifiers
Neural Processing Letters
| Hi-index | 0.00 |
Analyzing the characteristics of wood biomass gasification process comprehensively and considering the impact of gasification temperature as well as the amount of catalyst on gasification gas components, gas yield, gas production rate, the calorific value and gasification efficiency, sawdust gasification process model based on LSSVM (least squares support vector machine) was set up. Based on this model, a multi-objective optimization function was put forward between control parameters and gasification performance. Besides, the target value of control parameters was optimized. Sawdust gasification process model and optimized target value of control parameters was verified according to experimental data in literature [4]. The results showed that the model revealed good simulation effect and the target value of control parameters based on multi-objective optimization function was very close to experimental data which mean the method was effective. Therefore, it's possible to use the method to optimize the target value of control parameters in actual gasification process.